**Table 2.**

*Type 2 Diabetes - From Pathophysiology to Cyber Systems*

*Physiological factors to be considered while measuring HRV.*

**Physiological factors influencing on HRV**

*Quantification of HRV into time domain and frequency parameters along with Poincare plot.*

**4.1 Time and frequency domain, and non-linear analysis of HRV**

surement of autonomic nerve function [13].

(**Table 2**) [28] (**Figure 5**).

balance. HRV is quantified or measured by three methods; time domain, frequency domain and nonlinear analysis of short-term (5 mins) and long-term ECG (24 hrs.) recording (**Figure 4**). HRV test is an accurate quantitative and reproducible mea-

The time domain method measures the heart rate at any point either in time or in the intervals between successive QRS complex of a continuous ECG record. The interval between adjacent QRS complexes is known as normal-to normal (NN) interval. HRV time-domain indices quantify the amount of HRV observed during monitoring periods that may range from <1 min to >24 h. Time domain variables include the SDNN, SDANN, SDNNI, RMSSD, NN50, pNN50, HR Max − HR Min

Frequency domains variables (**Table 3**) are derived through many methods. Fast Fourier Transformation (FFT) is one the commonest methods to derive frequency components of HRV. Power spectrum derived through FFT is subsequently categorized into different bands of frequencies: VLF- (0.0033 to 0.04) Hz, LF- (0.04 to 0.15) Hz and HF- (0.15 to 0.4) Hz. Power spectral densities (PSD) are then plotted

*Heart rate variability (HRV). Ms: Milliseconds, bpm: Beats per minute, R-R int.: R-R interval.*

• Circadian rhythm • Respiration • Body mass index

• Body position • Physical fitness

**300**

**Figure 4.**

**Figure 3.**

• Age • Gender • Food ingestion

**Table 1.**

*Time domain variables of HRV with physiological significance.*

**Figure 5.**

*Time domain, frequency domain measurements and Poincare plot of HRV obtained through RMS Polyrite.*

in ms2 /Hz against preset frequencies. Power of the spectral bands are calculated in ms2 (absolute power) and in normalized units (n.u). For example, normalize unit of LF is calculated by the formula: [LF/total power-VLF] × 100. Power of LF and HF are established in short term analysis of HRV. Nonlinear method of HRV analysis (**Table 4**) through Poincare plot is done by plotting every RR interval against the prior interval consequently forming a scatter plot.


*"PNS AND SNS influences. #PNS influences.*

#### **Table 3.**

*Frequency domain variables of HRV with physiological significance.*


#### **Table 4.**

*Non-linear variables of HRV and physiological significance.*

#### **4.2 HRV in type 2 diabetes mellitus**

Reduced HRV is the earliest of sign CAN, reflecting impaired sympathetic and parasympathetic activity without apparent clinical signs and symptoms of CAN [29]. T2DM causes decrease in almost all HRV variables. In a systematic review and meta-analysis performed on 25 studies analyzing HRV in T2DM showed overall decrease in the HRV in patients with T2DM owing to reduction both sympathetic and parasympathetic nerve function [30]. In another systematic review done on eight studies showed SD1/SD2, SDANN, and HF to have more sensitivity and specificity to detect autonomic dysfunction in diabetic patients indicating their potentials to be better diagnostic markers [31].

Abnormal nonlinear HRV variables are associated with diabetes or with the risk of development of T2DM [32]. Likewise, a review study revealed reduction in HRV variables, obtained through short-term and 24-hour ECG recording, in metabolic syndrome and T2DM [29].

There are no standard reference values for HRV variables to diagnose CAN [22]. However, Breder and Sposito proposes the diagnosis of CAN could be made on obtaining abnormal result in at least two of the following six parameters:

**303**

**Author details**

Sultana Ferdousi1

Shahbag, Dhaka, Bangladesh

provided the original work is properly cited.

\* and Phurpa Gyeltshen<sup>2</sup>

\*Address all correspondence to: sferdousiratna@bsmmu.edu.bd

1 Department of Physiology, Bangbandhu Sheikh Mujib Medical University,

2 Khesar Gyalpo University of Medical Sciences of Bhutan, Thimphu, Bhutan

© 2021 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

*Type 2 Diabetes Mellitus: Cardiovascular Autonomic Neuropathy and Heart Rate Variability*

HRV displays beat-to-beat variations caused predominantly by the interplay of PNS and SNS control on SA node. Decline in HRV is seen even before manifesting signs and symptoms of diabetic CAN. Reduced HRV is the earliest sign of CAN. CAN is one of the under diagnosed microvascular complications of T2DM caused by hyperglycemia induced neuronal damage. Almost all HRV variables are

, HF < 300 ms2

SDNN <50 ms, RMSSD <15 ms, PNN50 < 0.75%, LF < 300 ms2

*DOI: http://dx.doi.org/10.5772/intechopen.95515*

**5. Conclusion**

decreased in T2DM.

**Conflict of interest**

derived from 24-hour Holter ECG recording [33].

The authors declare no conflict of interest.

*Type 2 Diabetes Mellitus: Cardiovascular Autonomic Neuropathy and Heart Rate Variability DOI: http://dx.doi.org/10.5772/intechopen.95515*

SDNN <50 ms, RMSSD <15 ms, PNN50 < 0.75%, LF < 300 ms2 , HF < 300 ms2 derived from 24-hour Holter ECG recording [33].
